1. Technical Field
The present disclosure relates to the field of digital video analysis and encoding, particularly a method of detecting playfields and classifying shots in sports video.
2. Background
Watching sports video is a popular pastime for many people. Digital transmissions of sports video can be viewed on televisions directly or through set-top boxes, or on other devices such as personal computers, tablet computers, smartphones, mobile devices, gaming consoles, and/or other equipment. Digital recordings of sports video can be viewed on the same devices and viewing the digital recordings can begin at the start of a recorded event or midway through the event.
Automatic parsing of sports video based on visual and/or cinematographic cues can be used to identify segments of potential interest to a viewer, and/or points at which video on demand playback can begin. Visual cues, such as long shots, medium shots and close up shots, can be used to identify segments of the video where on-field events are occurring, or to distinguish on-field events from close up views of players, referees, balls, logos, or other items. Long shots frequently provide coverage of large areas of a playing surface, such as a playing field or court, and frequently identify periods of time during which activity on the field is at a maximum. Extended periods of play can comprise a sequence of long shots followed by medium and/or close up shots which signify the end of a play or highlight the contributions of key players. Detection of long shots can also aid in automatically identifying highlights from the video, and/or automatically summarizing video.
Some methods of classifying shots have been developed. For example, some existing methods learn and adjust to color variations of the playfield, but do not detect shot types based on color histograms of selected regions of frames or accumulate the histograms by determined shot types. In other existing methods, color histograms are accumulated over a random selection of frames, not a selection of frames determined by the shot type. Still other methods use a Gaussian mixture model to classify shots, but requires training time to determine peaks of histograms before shot classification can begin, which can be difficult if non-sports video is interspersed with the sports video, such as commercials or pregame analysis.